Happiness Essay

What makes a person happy? Happiness is an endless path in life. Everyone has a different opinion about what makes them happy. People have always been attentive to the issue of what makes humans happy. However, getting a large amount of money is a pursuit for many people, especially the young generation around the world. In the article, â€Å"Get Happy† by Walter Mosley, he states how, â€Å"Happiness is considered by most to be a subset of wealth† (87). Quote above explains how money is the first thing that comes in person’s mind that make them happy because with the money one can buy anything he wants.Money is one of the most important things in over lives because we need it to have a home to live in, food to eat, clothes to wear, and to get from here to there. That’s where the â€Å"money can buy happiness† phrase comes in because people believe that since money can buy everything it can buy happiness too. However, I disagree and believe that hap piness primarily comes from relationships. First of all, money cannot buy relationships in a person’s life. Family and friends are one of the most important sources of happiness for most people.It doesn’t matter how much money a person has, if he doesn’t have any family or friends that he can share with, then it doesn’t bring very much happiness. As Mosley stated in his article, â€Å"It [Money] can only buy bigger TVs and comelier sex partners.. † (87). above quote explains money can only buy stuff that can make a person temporary happy. For instance, some people are really rich but lonely because they have no one by their side, while others are poor but happy with their close friends and family.In my personal experience, I have a friend back in India who was very rich and his parents got everything he wanted. When my parents bought me a bicycle, his parents bought him a bike. It looked like he had a perfect life, but once I got to know him better ; I got to realize that the life I thought that was perfect because of money was actually not perfect. Whenever his parents came home they always fought about little things, they never eat dinner together and they don’t even care about their son. They didn’t have any connections between them.So it’s true doesn’t matter how much wealth one have but one can never buy happiness that comes from one’s family. Secondly, Money is limited, it cannot last forever. Money can end easily and it cannot be obtained easily either. Even if money could buy happiness, it would only be for a little because things tend to disappear at some point. On the other hand, strong family bonds will never disappear but will be always by one’s side, continuing to bring one happiness. In addition, Mosley states, â€Å"how most of those people [wealthy people] will lose that wealth before they die† (87).No matter how rich a person is but there always will be a time w here all the money from the person will be gone. For example, my dad told me a story about this guy who was very wealthy in India but because of too much money he was too proud of himself and started breaking relationships with other people. He got caught in fraud for his business and everything was taken by the government. And just like that all the money was gone and there was no one by his side. In the article, â€Å"If You’re happy and you know it, You’re in Third† by Adriana Barton, she states about athlete names Ms.Bahrke who got a third number in Olympic game and still says â€Å" I’m going to be ‘Mrs. Happy. [Getting married]’† (84). She wasn’t sad that she couldn’t get a first place but she was happy that she is getting married; it shows how relationships can bring happiness. Thus, money cannot buy happiness. Lastly, money can negatively consume in one’s life. Wealth is a good thing but it also can ruin a person’s life instead of giving someone happiness. Money is very addictive; even if person has a lot of money he will often never be satisfied with what he has.For example, instead, he will try to become wealthier and because of that he may not have time for his family or friends and will start losing relationships. It will have an effect on their children, and at the end, all he will have is money but no one else at his side. In the article, â€Å"What you don’t know makes you nervous,† by Daniel Gilbert, he states, â€Å"psychologists and economists now know that although the very rich are no happier than the merely rich†¦ † (80). the above quote states how most of the time people who has a lot money are the one that are not happy.If money makes a one happy then why wealthy people are are not happier than the poor people? The main reason is relationships. Wealthy people are so into making money that it makes them so blind that they cannot see the h appiness that their family can bring to them. And at the end they have all the money but they don’t have any shoulders to cry on or to share the money, happiness with. While poor people might don’t have money but they have the family that takes care of each other which is most important happiness a person can have. Thus, relationships can bring a person long lasting happiness but money won’t.Too much money can make person’s life depressed instead of giving happiness. But family will always be there by one’s side. In conclusion, I don’t think that it? s somehow possible to â€Å"buy happiness†. Thus, we should be aware that it is friendships and family that truly bring us the happiness to which we aspire. Money might be able to make people temporarily happy but that’s not the point, the point is that it can’t buy anyone long lasting happiness. Being happy is an emotion it is something you sense, not something you buy. Tha t is why happiness is priceless. Works CitedBarton Adriana. â€Å" If You’re Happy and You Know It, You’re in Third. † America Now: Short Readings from Recent Periodicals. 9th ed. Ed. Robert Atwan. Boston: Bedford/St. Martin’s,2011. 79-81. Print. Gilbert, Daniel. â€Å"What You Don’t Know Makes You Nervous. † America Now: Short Readings from Recent Periodicals. 9th ed. Ed. Robert Atwan. Boston: Bedford/St. Martin’s, 2011. 79- 81. Print. Mosley Walter. â€Å"Get Happy. † America now: Short Readings From Recent Periodicals. 9th Ed. Ed. Robert Atwan. Boston: Bedford/St. Martin’s, 2011. 79-81. Print.

To Kill a Mockingbird Novel

To Kill a Mockingbird is a novel about growing in the 1930s in the Southern United States. Scout Finch lives with her brother Jem and their father Atticus (a lawyer) in the town of Maycomb, Alabama. Maycomb is a small town, and every family has its social standing depending on where they live, who their parents are, and how long they have lived in Maycomb. Atticus raises his children by himself, with the help of neighbors and a black housekeeper named Calpurnia. Scout is a tomboy who prefers to solve her differences with her fists. She tries to make sense of a world that demands that she act like a lady, a brother who criticizes her for acting like a girl, and a father who accepts her just as she is. Scout hates school, gains most of her education on her own and from her father. Scout and Jem understand their neighborhood and town. The only neighbor they do not understand is Arthur Radley, nicknamed Boo, who never comes outside. When Dill, another neighbor's nephew, starts spending summers in Maycomb, the three children begin an obsessive quest to lure Boo outside. Scout and Jem discover that their father is going to represent a black man named Tom Robinson, who is accused of raping and beating a white woman. Suddenly, Scout and Jem have to deal with racial slurs and insults because of Atticus' role in the trial. During this time, Scout has a very difficult time restraining from fighting, which gets her in trouble with her aunt and uncle. Even Jem loses his temper a time or two. After destroying a neighbor's plants, Jem is sentenced to read to her every day after school for one month. As the trial gets closer, their aunt comes to live with them. Read also  How Powerful Do You Find Atticus Finch’s Closing Speech? During the last summer, Tom is tried and convicted even though Atticus proves that he could not have done the crime. In the process of trying the case, Atticus accidentally offends Bob Ewell, a nasty drunk whose daughter accused Tom. In spite of Tom's conviction, Ewell vows revenge on Atticus and the judge. All three children are stunned by the jury's decision, and Atticus tries to explain why the jury's decided that way. After the trial, Scout attends one of her aunt's Missionary Society meetings. Atticus interrupts the meeting to report that Tom Robinson had been killed in an escape attempt. Scout learns valuable lessons that day. Things slowly return to normal, and Scout and Jem realize that Boo is no longer the center of their curiosity. The story appears to be winding down, when Bob Ewell starts making well on his threats of revenge. Scout is in the Halloween pageant at school, Jem agrees to take Scout to the school. After embarrassing herself on-stage, Scout leaves her costume on for the walk home with Jem. On the way home, the children hear noises, but disregard them as a friend who scared them on their way to school that evening. They are attacked, and Scout really cannot see out of her costume. She hears Jem being pushed away, and she feels arms squeezing her. Jem breaks his arm during this attack. Scout gets just enough of a glimpse out of her costume to see a stranger carrying Jem back to their house. The sheriff arrives at the Finch and announces that Bob Ewell has been found dead under the tree where the children were attacked, believing that he had fallen on his own knife. Scout realized that the stranger was Boo Radley, and that Boo is responsible for killing Ewell, and saving her and Jem's lives. Atticus' tries to get the sheriff to press charges against Boo, but he refuses. Scout agrees with his decision and explains it to her father. Boo sees Jem one more time and then asks Scout to take him home. With Boo safely home, Scout returns to Jem's room where Atticus is waiting. He reads her to sleep and then waits for Jem to wake up. I believe the main reasons that this book was banned were because of the language that was used, along with the racist implications toward the government. I also believe that it showed an unjust court system.

Case study Essay Example | Topics and Well Written Essays - 1500 words - 18

Case study - Essay Example The second category is active sport tourism. This category includes activity holidays and active events. The third category is event sport tourism. This includes the active and passive participation in sporting events (Gibson, 1998). Gibson (1998,p.49), further conceptualizes sport tourism to be in three distinct areas; traveling to take part in a sporting event; traveling to watch a sport; or travelling to celebrate, worship, or venerate a sport. More recent definitions of sport tourism argue that it is more than a two dimensional synergetic phenomenon. In a more intricate definition, sport tourism is a social, economic and cultural phenomenon that arises from the unique interaction of activity, people, and place (Weed & Bull, 2004, p. 37). Weymouth and Portland are located on the south coast of England. This area provides some of the best sailing waters in the UK. In addition to this, the area has facilities on land to complement the sailing activities that take place. Before the 2012 Olympic games, the area already had world class facilities but some few enhancements were necessary to ensure that the facilities were suitable enough to host the sailing competition during the main Olympics and the Paralympics (london2012.com). Considering that sailing is both a competitive and leisure sporting event, there were several types of sport tourist expected to be in the area during the Olympic period. Gibson conceptualizes sport tourism to be in three distinct areas; travelling to take part; travelling to watch; or travelling to celebrate, worship or venerate a sport. From his conceptualization, the types of tourists that can and were attracted to visit Weymouth and Portland

Argumentative Essay Example | Topics and Well Written Essays - 1250 words

Argumentative - Essay Example Any new idea has excitement that comes with it, (Shelly, and Vermaat 2011, p112). Sometimes this excitement causes people to fail to look into the long-term. Take the internet, for example, the innovation of cruise missiles. Every nation on earth has a mandate to protect her citizens. This mandate includes making the necessary steps to make sure the citizens feel safe enough in the nation. This has caused military, technological advancements to increase. It is disturbing that cruise missiles are made with a human enemy in mind. There is a genuine need for protection. Human to human enmity is not farfetched. That does not change the fact that war anticipation is not peaceful solution. In as much as the protection is beneficial, that protection does not mean that the sanctity of human life be compromised. We see more and more weapons of mass destruction, being made. There are better ways to anticipate peace and keep with world united other that regular tests devastating weapons, (USA C ongress, p16). Technology is celebrated, because it has increase efficiency. Say, for example, in the point above. It is possible to instigate an attack in another country without necessarily being there physically. However, efficiency is not absolute. Efficiency has its place. The solutions that come with technology must reflect the values that protected the lives of those who come up with these technological solutions. In other words, if the technological solution is not pro-life, it then should not be taken in as a solution. The information age is here with us. People can purchase any product while still in their bedrooms. Navigating through a website is the new form of window shopping. Transactions happen at the click of a mouse. This, has been hailed, as a major breakthrough in that it saves time. There is no doubt that online shopping and ecommerce saves time and can be cost effective in that sense. However, the traditional shopping involved a physical interaction with the sel ler, though it was time consuming. The essence of technology is to provide solutions so that life can be bearable and there can be happiness. However, the physical interaction with a buyer has no substitute. It seems that technology has lessened the value of human to human interaction, (Graham, 2008). The earlier people leave each other the more convenient’ the deal was. It seems we are witnessing a culture where humans are working hard for less interactions and more centered achievements. The faster the egocentric desires, are met, the more convenient life is to us. All this, is done in anticipation that the world shall become a better place. However, the world is experiencing the highest suicide rate ever. Even the most services have been digitized, people are losing hope. There are many and numerous instances where technology has led to saving lives. Take for instance, the discovery of better intensive care unit systems and strong vaccines. Such discoveries have led to sav ing lives. The problem is technological convenience in the world does not translate into solutions or personal happiness. Rather, there are many instances that technology has proved to be more harmful that useful. When internet, was launched, there was a lot of hope that communication world be fast, and that international boundaries would be surpassed. Indeed the internet

Can technology benefit education Essay Example | Topics and Well Written Essays - 1250 words

Can technology benefit education - Essay Example ng system in colleges and universities plays an important role in the availing information for coursework to students registered with the institutions. The tutors upload the necessary information on the developed program and the students access it with the help of an individual username and a password (Selwyn, 77). The use of technology in this manner is convenient to both the learner and the tutor because both parties are relieved from hard copies as sources of information. The use of hard copy is bulky in terms of carrying and expensive to purchase. Printing out of information on soft copy is cost effective compared to purchasing a published book. For these reasons, the availability of coursework in the form of soft copy through an E-learning system is beneficial in educating the students because it is conveniently accessible and inexpensive. Implementation of digitized library systems in secondary and tertiary levels of education simplifies book searching, borrowing and returning. Instances where additional research or extensive reading on a discipline is a recommendation, visiting the library is inevitable. The automated access to published books by the tutee aids in proper management of time. The utilization of technology in this way wards off wastage of time by availing books with ease putting the learner at an advantage. In this case, technological education in light of time is effective. The use of E-mails to communicate and face-face platforms such as Skype to name a few allow real-time interaction between the student and educator. For this reason, distance learning is popular. In both secondary and tertiary levels of education, individuals are able to learn with convenience by interacting with the tutor through a webcam or messenger irrespective of their location. Assignments and assessments are coordinated through e-mails and websites. Examinations and assessments are carried out on real-time basis where the learner submits and receives results when

Police academy or Finger printing or Federal, state local agency Essay

Police academy or Finger printing or Federal, state local agency qualifications chose one of the three topic that you feel comfortable with - Essay Example cted the practice of law enforcement, the history of the technique, legal and ethical issues involving the use of the technique, practical implications of the technique for law enforcement personal at various levels, and future prospects for fingerprinting must be analyzed. Finger prints have had many definitions throughout history, and have been used in art, science, and law enforcement. The contemporary definition of a fingerprint states that a finger print can be defined as the unique pattern created by the friction ridges on all or part of a digit, or finger (â€Å"Glossary†, 2009). The term friction ridge is not intuitive. Friction ridges rare the scientific name for the raised portion of the outermost layer of skin, called the epidermis, that forms the unique shapes found in fingerprints (â€Å"Glossary†, 2009). Friction ridges form on the fingers, palm, toes, and soles of the feet of the fetus before it is born (Cowger, 1992, p.1). Despite the growth that occurs in childhood and adolescence, the patter of the friction ridges does not change, and thus provides the only physical characteristic of human kind with the specificity to identify an individual. Human beings first noticed fingerprints in prehistoric times. The earliest fingerprints are included as decorative elements in cave paintings found in Nova Scotia that date back thousands of years (German, 2006). In ancient Babylon, merchants recognized that though many people have similar patterns, no two individuals have the same exact fingerprint. These merchants used fingerprints as official seals on business agreements, much as contemporary merchants would use a Federal Identification or Social Security number (German, 2006). Similar methods of using fingerprints to identify merchants and government officials were found in fourteenth century Persia and China (German, 2006). These cultures made use of the impressions left by fingerprints as a tool for identification on documents, but did little

Corporation Finance Assignment Example | Topics and Well Written Essays - 5000 words

Corporation Finance - Assignment Example These firms are targeted owing to ever growing demand for metals because of its high value that has constantly soar especially iron and aluminum, that up to present is being recycled whenever possible as a result of the value of their physical and chemical characteristics. The Business will be of great importance to its clients (processing companies) as it will save them energy and resources in collecting and treating the scrap metals. 1.3 MAGEMENT AND ORGANIZATION PLAN Eco-Super Scrap Metals LTD management will consist of many employees and self-employed persons contracted by the company. However, the executive management team will consist of general manager, accountant, casual laborers and permanent and pensionable employees such trainers, supervisors and coordinators, who will be manning the sites and training other employees on health and safety of when working within the company. 1.4 OPERATIONAL AND PRODUCTION PLAN The premise and other basic utilities such as operational servic es like electricity will be acquired on rental basis rental bill being paid on monthly terms. However, the business machinery and fix assets such as, treatment plants and other essential paraphernalia like computers, printers, photocopier and furniture will be owned by the business as the initial capital fixed assets. 1.5 FINANCIAL PLAN The starting Capital will be $1,000,000 inclusive of operational capital of $ 700,000. The businesses will obtain this initial capital from owners’ personal savings, amounting to $. 200,000 and a funding through bank loan of $ 800,000. 2.0 BUSINESS DESCRIPTION Eco-Super Scrap Metals LTD main business will be collecting the scrap metals from the environment and treating these metals before trading them to metal processing company. In doing so, it will also be committed to clean environment, making it safety for habitation 2.1 Business Name The business will operate under the name Eco-Super Scrap Metals LTD. This business, given that it is not a new business idea in the region, will be subjected to competition from other firms of similar business. The business commences its operation soon after meeting the qualifications requirements imposed by the regulation bodies and registrar of business. 2.2 Physical Location Eco-Super Scrap Metals LTD will be concern with collecting the scrap metals from the building sites and also will have a centered point for collection in East London next to A13 motorway, to facilitate easy connection with the city. 2.2.1 Mission Statement The mission of the business is to collect and sell treated scrap metals to metal processing firms, before it goes to landfill, and in doing so, clean the environment for sustainability for habitation. 2.2.2 Vision To be the leading scrap metal industry in the entire Europe and outside the continent 2.2.3 Core Values i. Quality- The business main concern is on its customers and environment and so will strive to serve them diligently and upgrading the environment in its effort to be excellent through evaluation and continuous improvement. ii. Efficiency- Being efficient and effective in our mode of operation and give the best at all the time. iii. Passion- Concentrating on the work we do in both our minds and heart to give the best. iv. Accountability- Taking responsibility of our actions

Training and Development Task 1 Essay Example | Topics and Well Written Essays - 2000 words

Training and Development Task 1 - Essay Example irectly, there are safety precautions that must be in place, and observed with utmost care as demanded by most of the occupational health and safety regulations (Brumitt & Human Kinetics (Organization), 2010). In many industries, people have succumbed injuries caused by poor human resource management. Professionalism, besides safety management is a crucial consideration as far as managing human input is concerned. Employees should be adequately equipped with the appropriate skills required in various production areas, which calls for sufficient implementation of training and talent development measures. The proper establishment of favorable working conditions is also important to this pursuit – management of human resource in the residential roofing installation company. When the employees are safe and enhanced professionally, they would eventually attain the highest performance ratios (Landy & Conte, 2010). To initiate the training and development programs successfully, a needs assessment should be conducted effectively. The management should conduct the systematic process of addressing and determining the needs emanating from the current and desired conditions. To identify the need appropriately, the measurement of the wanted (future) conditions as well as the current conditions is imperative. This would help notify the needs of the operational situations that need to be tackled in the process of human resource management. Numerous requirements are needed to curb the challenges faced by the company to ensure employees are safe and well cared for during their operations such as the use of safety tools besides training. Conducting the needs assessment, prior to training, helps the company in many ways. For instance, it enables the company to identify the prospective needs for the production process. The needs assessment procedures also establish the nature and causes of needs experience d by the company. Lastly, by the realization of the needs, their causes and

Faith and Evolution Essay Example for Free

Faith and Evolution Essay Erik Easler Professor Pelphrey Writing Seminar October 27, 2011 Faith and Evolution In the Catholic Christian religion, the essential belief is that Jesus of Nazareth was the son of god God who was born of the Virgin Mary, became man, and died on the cross for all of man kinds sins. However, many people who are catholic Vatholic believe that God created the Earth six thousands of years ago, a belief referred to as creationism. One particular group of Catholics Christans called Baptists, do not question the authority of the bible Bible and believe it word for word, and this is here I tend to disagree. I was born and raised a catholicCatholic, and I still believe with all my heart and soul that Jesus was in fact the son of god God and do my best to follow the morals taught in the good book. When it comes to what I believe in terms of how the Earth was made created though, the theory of evolution seems to make a lot more sense to me. With all the logical points that it makes, I feel believe like it has more truth to it than the theory of creationism, ; after all, it was not god God who wrote the bibleBible. Essentially, I believe that you can continue to have aith for Jesus, God, and the morality of the bible without believing that every last word is one hundred percent accurate. In other words, I believe it is possible for a Catholic to still be faithful even if they also think that Darwins theory is true. The theory of evolution was started by a man named Charles Darwin. Darwin was born on February 12th of 1809 in Shrewsbury, Shropshire. He was born into a wealthy family that had many connections. His maternal grandfather was china manufacturer Josiah Wedgwood, while his paternal grandfather was Erasmus Darwin, who appened to be one of the leading intellectuals of 18th century England. Darwins initial plan was to pursue a medical career at Edinburgh University, but later switched to divinity at Cambridge. In 1831, Darwin Joined a voyage on the survey ship HMS Beagle. During this time period, almost all Europeans believed in the creationism belief that the world was created by God in seven days as described in the bibleBible. On this voyage, Darwin read a book called Principles of Geology which suggested that the fossils found in rocks were actually evidence of animals that had lived many thousands or millions of years ago. Lyells argument was reinforced in Darwins own mind by the wide variety of animal life and the many geological features he saw during this trip. The breakthrough in Darwins ideas came on the Galapagos Islands, which is about 500 miles west of the continent of South America. While on these islands, Darwin observed that each island had its own form of finch, all of which were closely related but differed in important ways. This sparked many new ideas in Darwins mind that eventually lead him to coming up with a theory that would change the way we think about things. When Darwin ventually got back to England in 1836, he worked endlessly trying to use his observations he had made to put the pieces of the puzzle together to discover how species evolved. Intluenced by the works ot a man named Malthus, Darwin proposed his theory of evolution through a process called natural selection. Natural selection basically Just means that animals and plants best suited to their environment are the most likely to survive and reproduce, passing on the characteristics which helped them survive to their offspring. Through this, new species develop over time. Darwin worked on this for about twenty years and made a Joint announcement with another naturalist named Alfred Wallace who had similar ideas about their discovery in 1858. A year later, Darwin published the book On the Origin of Species by Means of Natural Selection. This book at the time was extremely controversial, because it suggested that man had evolved from another animal such as an ape. Darwin was criticized by many people, especially by the church, because his theory had destroyed the prevailing orthodoxy on how the world was created. However, Darwins ideas later gained currency and have become the modern day orthodoxy. Even after his death on April 19th of 1882, today his ideas are proving to be very accurate. Many Catholics Christisns today still believe in the methods of creationism, but those that believe in creationism, even if they know about evolution, continue to believe otherwise because they believe it is a test of their faith from God. As a Catholic myself, I can fully understanding being respectful to God because I do my best every day to give him thanks for what I have almost every day in some way, shape, or form. However, in the commandment Thou shall not lie I am not perfect in this regard, but I follow it the best I possibly can. Through it I am always looking to seek the truth, and while ignorance itself is not lying, it can still mislead in a similar way. For example, back in the renaissance days of scientific oppression, many other great minds of the time, in the same way that Darwin was in his time, were attacked by the church for going against the Catholic belief even though they had solid proof through their experiments. Galileo for example was attacked by the church for believing that our solar system was actually heliocentric, instead of believing the common belief that everything revolved around the world. Despite the fact that Galileo had proof of this through many experiments, the church refused to open itself up to the new ideas all because one of the biblical authors thought that everything revolved around the Earth. For these men who were ahead of their time, it was never a matter of disproving the church; it was a matter of proving what is true. Perhaps if more Catholics learned to be less adamant and more open about beliefs, than I think it is quite possible that if we had been more open back then to different ideas, we could be in a far more advanced technological world today. Along with not being very pen about new views, the church along with its creationist believers also seems to ignore the facts that back up Darwins theory. Five of the most essential of these points include the universal genetic code, the fossil record, genetic commonalities, common traits in embryos, and bacterial resistance to antibiotics. While there are many other strong points that also back up the Theory of Evolution, these five sum up most of the previously stated definition of the theory. Be sure to introduce who came up with this proof and what it entails. Essentially, you should come to terms with it. According to the universal genetic code All cells on Earth, from white blood cells to simple bacteria, all have a genetic code that can be determined (5 proofs). This seems to suggest that if all life has a genetic code that has a composition that can be determined, then perhaps all ot lite did in tact descend trom common ancestry. Since Darwins theory suggests that all life came from a common ancestor, this point backs up what Darwin was trying to say quite nicely. Along with the universal genetic code, one must also consider the fossil record. This record states that the simplest fossils will be found in the oldest rocks. There is also a smooth and gradual transition from one form of life to another (5 proofs). This suggests that since the simplest forms of life were found in the oldest rocks, then these simple forms of life must have been the first forms of life which adapted to their surroundings over time. This point along with the last one also does an exceptional Job of giving the Theory of Evolution some reinforcement. To continue off of what the fossil record was stating one also should consider genetic commonalities. Genetic commonalities consider that Human beings have approximately 96% of genes in common with chimpanzees, about 90% of enes in common with cats, 80% with cows, 75% with mice, and so on (5 proofs). While this does not necessarily prove that we descended from chimps, it definitely seems to suggest that the species listed all had some sort of common ancestor before they naturally developed into what they are today. This points further backs up Darwins idea that all life came from a common ancestor. To extend off of the topic of genetic commonalties, one must also consider some of the common traits that are found in embryos. Common traits that are found suggest that Humans, dogs, snakes, fish, monkeys, etc. re all considered chordates because they belong to the phylum Chordata. One of the features of this phylum is that, as embryos, all these life forms have gill slits, tails, and specific anatomical structures involving the spine. For humans in particular, the gill slits reform into the bones of the ear and Jaw at a later stage in development (5 proofs). All this says is that initially, all chordate embryos seem to strongly resemble each other. Pigs for example, which also come from the phylum Chordata, are often dissected in many biology classes due to how similar their embryos are to humans. What this also seems to infer is that these common characteristics could only be possible if all members of the Chordata phylum came from a common ancestor, which again reinforces Darwins idea. Finally, the last of these five essential points is that one has to consider how bacteria over time build up resistances to antibiotics. According to this point Bacteria colonies can only build up a resistance to antibiotics through evolution. In every colony of bacteria, there are a tiny few individuals which are naturally resistant to certain antibiotics. This is due to the random nature of mutations (5 points). When an antibiotic is applied, the initial inoculation kills most of the bacteria, and leaves behind only a few cells which happen to have the mutations necessary to resist the antibiotics. When these bacteria reproduce, they pass down their mutations characteristics and these future generations become resistant to the specific antibiotic. This specific example is probably one of the best because it is essentially what natural selection is, which a big part of Darwins theory is. All the bacteria that can survive this do and pass down their genes, and whatever else dies out. With ll of this in mind it is also important to consider some of the points that creationism makes so that one does not appear close minded to evolution either. Creationism is one of the oldest and most believed theories in the world. Generally speaking, it is the belief that God created the world in seven days. The greatest argument that creationists nave to otter is that all t li e seems designed, and scientists come to terms with why that is. For example, the trees and plants provide oxygen for animals and people, the animals and people provide the carbon dioxide for the trees and plants. Another good point they make is that the minds of people are all different from one another. For example, Just because man is all the same race, that does not mean we all think the same way. The creationists explanation for this is that it is all due to Gods divine intervention. In conclusion, I believe that evolution is the most logical explanation for how life came to be despite some of the good points that creationists make. As a catholic, I feel that I have the free will to believe this because nothing in the Ten Commandments or and golden rule states that the bible is one hundred ercent accurate.

Case analysis for Bank of America Essay Example for Free

Case analysis for Bank of America Essay Expand current app to include basic credit card and mortgage functions to increase market share of expanding mobile transaction market and shift customer activity to cost-effective channels. BOA’s entrance into local mobile payment and person-to-person P2P mobile shopping market (tap a large and growing market that currently lacks the regulation of banks and â€Å"added security†. I would like to divide strategy into two parts, short term and long term. The short term strategy is to solve the problem that how we define our market, and define population to be targeted with mobile strategy. Retain existing functionality. Enhance current app by adding basic credit card and mortgage features (increase passive customer engagement and minimize complexity). Increased customer engagement and cross-selling to make sure increasing transactions and save money. The long term strategy has three steps to executive. (1 Integrate Credit Card and Mortgage business into current Bank of America Mobile App. (2 Introduce Bank of America e-commerce app which includes local mobile payment and person to person capabilities. (3 Expand to international markets using existing mobile apps to create â€Å"virtual banking† regardless of physical branch presence. For local mobile payment, Bank of America should reduce transaction cost to Bank of America and merchants. Merchants reduce costs associated with current point of sale credit card services. Instant access via Bank of America e-commerce to business accounts and transaction history. Eliminating more expensive consumer and merchant transactions could save cost to Bank of America. For person-to-person, it should cut out the middleman which means reduced transactional costs. Secure payment system that is regulated and insured like a bank, unlike the currently the only established competitor,  PayPal. P2P market has a large potential for growth, estimate 2.4 billion e-commerce transaction in 2014 and 78 million active PayPal users, 3 billion â€Å"under-banked† consumers worldwide. The benefits of its app are at following sentences. 1) Leverage Bank of America as first online and mobile bank. 2) Cost efficient way to provide additional services to existing consumers and reach previously unreachable customers. 3) Without the existing company, PayPal, there is a few competitors in this market. 4) Costs include programming and maintenance of application after roll-out. There are other additional benefits. 1) New customers poached from other bank is 38 million transactions in 2010 and 119 in 2014. 2) Expand its reach into mobile transaction market as all customer groups experience increased convenience and streamlining of banking needs. 3) App for free = limits the barriers to entry. 4) Enhance features increase the likelihood of customers finding value in mobile banking. Bank of America’s market share of mobile transactions will increase as credit card and mortgage customers from all groups utilize the app and extend their activities with the bank (as seen in Bank of America’s lessons from online banking). Incremental transactions made by mobile customers will come at a reduced expense to Bank of America.

Development of Intelligent Sensor System

Development of Intelligent Sensor System Chapter 1 1.1 Introduction What is Automation? Automation in general, can be explained as the use of computers or microcontrollers to control industrial machinery and processes thereby fully replacing human operators. Automation is a kind of transition from mechanization. In mechanization, human operators are provided with machinery to assist their operations, where as automation fully replaces the human operators with computers. The advantages of automation are: Increased productivity and higher production rates. Better product quality and efficient use of resources. Greater control and consistency of products. Improved safety and reduced factory lead times. Home Automation Home automation is the field specializing in the general and specific automation requirements of homes and apartments for their better safety, security and comfort of its residents. It is also called Domotics. Home automation can be as simple as controlling a few lights in the house or as complicated as to monitor and to record the activities of each resident. Automation requirements depend on person to person. Some may be interested in the home security while others will be more into comfort requirements. Basically, home automation is anything that gives automatic control of things in your house. Some of the commonly used features in home automation are: Control of lighting. Climate control of rooms. Security and surveillance systems. Control of home entertainment systems. House plant watering system. Overhead tank water level controllers. Intelligent Sensors Complex large-scale systems consist of a large number of interconnected components. Mastering the dynamic behavior of such systems, calls for distributed control architectures. This can be achieved by implementing control and estimation algorithms in several controllers. Some algorithms manipulate only local variables (which are available in the local interface) but in most cases, algorithms implemented in some given computing device will use variables which are available in this devices local interface, and also variables which are input to the control system via remote interfaces, thus rising the need for communication networks, whose architecture and complexity depend on the amount of data to be exchanged, and on the associated time constraints. Associating computing (and communication) devices with sensing or actuating functions, has given rise to intelligent sensors. These sensors have gained a huge success in the past ten years, especially with the development of neural network s, fuzzy logic, and soft computing algorithms. The modern definition of smart or intelligent sensors can be formulated now as: ‘Smart sensor is an electronic device, including sensing element, interfacing, signal processing and having several intelligence functions as self-testing, self-identification, self-validation or self-adaptation. The keyword in this definition is ‘intelligence. The self-adaptation is a relatively new function of smart sensors and sensor systems. Self-adaptation smart sensors and systems are based on so-called adaptive algorithms and directly connected with precision measurements of frequency-time parameters of electrical signals. The later chapters will give an elaborate view on why we should use intelligent sensors, intelligent sensor structure, characteristics and network standards. Chapter 2 2.1 Conventional Sensors Before talking more on intelligent sensors, first we need to examine regular sensors in order to obtain a solid foundation on which we can develop our understanding on intelligent sensors. Most of the conventional sensors have shortcomings, both technically and economically. For a sensor to work effectively, it must be calibrated. That is, its output must be made to match some predetermined standard so that its reported values correctly reflect the parameter being measured. In the case of a bulb thermometer, the graduations next to the mercury column must be positioned so that they accurately correspond to the level of mercury for a given temperature. If the sensor is not calibrated, the information that it reports wont be accurate, which can be a big problem for the systems that use the reported information. The second concern one has when dealing with sensors is that their properties usually change over time, a phenomenon knows as drift. For instance, suppose we are measuring a DC current in a particular part of a circuit by monitoring the voltage across a resistor in that circuit. In this case, the sensor is the resistor and the physical property that we are measuring the voltage across it. As the resistor ages, its chemical properties will change, thus altering its resistance. As with the issue of calibration, some situations require much stricter drift tolerances than others; the point is that sensor properties will change with time unless we compensate for the drift in some fashion, and these changes are usually undesirable. The third problem is that not only do sensors themselves change with time, but so, too, does the environment in which they operate. An excellent example of that would be the electronic ignition for an internal combustion engine. Immediately after a tune-up, all the belts are tight, the spark plugs are new, the fuel injectors are clean, and the air filter is pristine. From that moment on, things go downhill; the belts loosen, deposits build up on the spark plugs and fuel injectors, and the air filter becomes clogged with ever-increasing amounts of dirt and dust. Unless the electronic ignition can measure how things are changing and make adjustments, the settings and timing sequence that it uses to fire the spark plugs will become progressively mismatched for the engine conditions, resulting in poorer performance and reduced fuel efficiency. The ability to compensate for often extreme changes in the operating environment makes a huge difference in a sensors value to a particular applic ation. Yet a fourth problem is that most sensors require some sort of specialized hardware called signal-conditioning circuitry in order to be of use in monitoring or control applications. The signal-conditioning circuitry is what transforms the physical sensor property that were monitoring (often an analog electrical voltage that varies in some systematic way with the parameter being measured) into a measurement that can be used by the rest of the system. Depending upon the application, the signal conditioning may be as simple as a basic amplifier that boosts the sensor signal to a usable level or it may entail complex circuitry that cleans up the sensor signal and compensates for environmental conditions, too. Frequently, the conditioning circuitry itself has to be tuned for the specific sensor being used, and for analog signals that often means physically adjusting a potentiometer or other such trimming device. In addition, the configuration of the signal-conditioning circuitry tends to be unique to both the specific type of sensor and to the application itself, which means that different types of sensors or different applications frequently need customized circuitry. Finally, standard sensors usually need to be physically close to the control and monitoring systems that receive their measurements. In general, the farther a sensor is from the system using its measurements, the less useful the measurements are. This is due primarily to the fact that sensor signals that are run long distances are susceptible to electronic noise, thus degrading the quality of the readings at the receiving end. In many cases, sensors are connected to the monitoring and control systems using specialized (and expensive) cabling; the longer this cabling is, the more costly the installation, which is never popular with end users. A related problem is that sharing sensor outputs among multiple systems becomes very difficult, particularly if those systems are physically separated. This inability to share outputs may not seem important, but it severely limits the ability to scale systems to large installations, resulting in much higher costs to install and support multiple r edundant sensors. What we really need to do is to develop some technique by which we can solve or at least greatly alleviate these problems of calibration, drift, and signal conditioning. 2.2 Making Sensors Intelligent Control systems are becoming increasingly complicated and generate increasingly complex control information. Control must nevertheless be exercised, even under such circumstances. Even considering just the detection of abnormal conditions or the problems of giving a suitable warning, devices are required that can substitute for or assist human sensation, by detecting and recognizing multi-dimensional information, and conversion of non visual information into visual form. In systems possessing a high degree of functionality, efficiency must be maximized by division of the information processing function into central processing and processing dispersed to local sites. With increased progress in automation, it has become widely recognized that the bottleneck in such systems lies with the sensors. Such demands are difficult to deal with by simply improvising the sensor devices themselves. Structural reinforcement, such as using array of sensors, or combinations of different types of sensors, and reinforcement from the data processing aspect by a signal processing unit such as a computer, are indispensible. In particular, the data processing and sensing aspects of the various stages involved in multi-dimensional measurement, image construction, characteristic extraction and pattern recognition, which were conventionally performed exclusively by human beings, have been tremendously enhanced by advances in micro-electronics. As a result, in many cases sensor systems have been implemented that substitute for some or all of the intellectual actions of human beings, i.e. intelligent sensor systems. Sensors which are made intelligent in this way are called ‘intelligent sensors or ‘smart sensors. According to Breckenridge and Husson, the smart sensor itself has a data processing function and automatic calibration/automatic compensation function, in which the sensor itself detects and eliminates abnormal values or exceptional values. It incorporates an algorithm, which is capable of being altered, and has a certain degree of memory function. Further desirable characteristics are that the sensor is coupled to other sensors, adapts to changes in environmental conditions, and has a discriminant function. Scientific measuring instruments that are employed for observation and measurement of physical world are indispensible extensions of our senses and perceptions in the scientific examination of nature. In recognizing nature, we mobilize all the resources of information obtained from the five senses of sight, hearing, touch, taste and smell etc. and combine these sensory data in such a way as to avoid contradiction. Thus more reliable, higher order data is obtained by combining data of different types. That is, there is a data processing mechanism that combines and processes a number of sensory data. The concept of combining sensors to implement such a data processing mechanism is called ‘sensor fusion 2.2.1 Digitizing the Sensor Signal The discipline of digital signal processing or DSP, in which signals are manipulated mathematically rather than with electronic circuitry, is well established and widely practiced. Standard transformations, such as filtering to remove unwanted noise or frequency mappings to identify particular signal components, are easily handled using DSP. Furthermore, using DSP principles we can perform operations that would be impossible using even the most advanced electronic circuitry. For that very reason, todays designers also include a stage in the signal-conditioning circuitry in which the analog electrical signal is converted into a digitized numeric value. This step, called analog-to-digital conversion, A/D conversion, or ADC, is vitally important, because as soon as we can transform the sensor signal into a numeric value, we can manipulate it using software running on a microprocessor. Analog-to-digital converters, or ADCs as theyre referred to, are usually single-chip semiconductor devices that can be made to be highly accurate and highly stable under varying environmental conditions. The required signal-conditioning circuitry can often be significantly reduced, since much of the environmental compensation circuitry can be made a part of the ADC and filtering can be performed in software. 2.2.2 Adding Intelligence Once the sensor signal has been digitized, there are two primary options in how we handle those numeric values and the algorithms that manipulate them. We can either choose to implement custom digital hardware that essentially â€Å"hard-wires† our processing algorithm, or we can use a microprocessor to provide the necessary computational power. In general, custom hardware can run faster than microprocessor-driven systems, but usually at the price of increased production costs and limited flexibility. Microprocessors, while not necessarily as fast as a custom hardware solution, offer the great advantage of design flexibility and tend to be lower-priced since they can be applied to a variety of situations rather than a single application. Once we have on-board intelligence, were able to solve several of the problems that we noted earlier. Calibration can be automated, component drift can be virtually eliminated through the use of purely mathematical processing algorithms, and we can compensate for environmental changes by monitoring conditions on a periodic basis and making the appropriate adjustments automatically. Adding a brain makes the designers life much easier. 2.2.3 Communication Interface The sharing of measurements with other components within the system or with other systems adds to the value of these measurements. To do this, we need to equip our intelligent sensor with a standardized means to communicate its information to other elements. By using standardized methods of communication, we ensure that the sensors information can be shared as broadly, as easily, and as reliably as possible, thus maximizing the usefulness of the sensor and the information it produces. Thus these three factors consider being mandatory for an intelligent sensor: A sensing element that measures one or more physical parameters (essentially the traditional sensor weve been discussing), A computational element that analyzes the measurements made by the sensing element, and A communication interface to the outside world that allows the device to exchange information with other components in a larger system. Its the last two elements that really distinguish intelligent sensors from their more common standard sensor relatives because they provide the abilities to turn data directly into information, to use that information locally, and to communicate it to other elements in the system. 2.3 Types of Intelligent Sensors Intelligent sensors are chosen depending on the object, application, precision system, environment of use and cost etc. In such cases consideration must be given as to what is an appropriate evaluation standard. This question involves a multi-dimensional criterion and is usually very difficult. The evaluation standard directly reflects the sense of value itself applied in the design and manufacture of the target system. This must therefore be firmly settled at the system design stage. In sensor selection, the first matter to be considered is determination of the subject of measurement. The second matter to be decided on is the required precision and dynamic range. The third is ease of use, cost, delivery time etc., and ease of maintenance in actual use and compatibility with other sensors in the system. The type of sensor should be matched to such requirements at the design stage. Sensors are usually classified by the subject of measurement and the principle of sensing action. 2.3.1 Classification Based on Type of Input In this, the sensor is classified in accordance with the physical phenomenon that is needed to be detected and the subject of measurement. Some of the examples include voltage, current, displacement and pressure. A list of sensors and their categories are mentioned in the following table. Category Type Dynamic Quantity Flow rate, Pressure, force, tension Speed, acceleration Sound, vibration Distortion, direction proximity Optical Quantities Light (infra red, visible light or radiation) Electromagnetic Quantities Current, voltage, frequency, phase, vibration, magnetism Quantity of Energy or Heat Temperature, humidity, dew point Chemical Quantities Analytic sensors, gas, odour, concentration, pH, ions Sensory Quantities or Biological Quantities Touch, vision, smell Table 2.3.1: Sensed items Classified in accordance with subject of measurement. 2.3.2 Classification Based on Type of Output In an intelligent sensor, it is often necessary to process in an integrated manner the information from several sensors or from a single sensor over a given time range. A computer of appropriate level is employed for such purposes in practically y all cases. For coupling to the computer when constructing an intelligent sensor system, a method with a large degree of freedom is therefore appropriate. It is also necessary to pay careful attention to the type of physical quantity carrying the output information to the sensor, and to the information description format of this physical quantity or dynamic quantity, and for the description format an analog, digital or encoded method etc., might be used. Although any physical quantities could be used as output signal, electrical quantities such as voltage are more convenient for data input to a computer. The format of the output signal can be analog or digital. For convenience in data input to the computer, it is preferable if the output signal of the sensor itself is in the form of a digital electrical signal. In such cases, a suitable means of signal conversion must be provided to input the data from the sensor to the computer 2.3.3 Classification Based on Accuracy When a sensor system is constructed, the accuracy of the sensors employed is a critical factor. Usually sensor accuracy is expressed as the minimum detectable quantity. This is determined by the sensitivity of the sensor and the internally generated noise of the sensor itself. Higher sensitivity and lower internal noise level imply greater accuracy. Generally for commercially available sensors the cost of the sensor is determined by the accuracy which it is required to have. If no commercial sensor can be found with the necessary accuracy, a custom product must be used, which will increase the costs. For ordinary applications an accuracy of about 0.1% is sufficient. Such sensors can easily be selected from commercially available models. Dynamic range (full scale deflection/minimum detectable quantity) has practically the same meaning as accuracy, and is expressed in decibel units. For example a dynamic range of 60dB indicates that the full scale deflection is 103 times the minimum detectable quantity. That is, a dynamic range of 60dB is equivalent to 0.1% accuracy. In conventional sensors, linearity of output was regarded as quite important. However, in intelligent sensor technology the final stage is normally data processing by computer, so output linearity is not a particular problem. Any sensor providing a reproducible relationship of input and output signal can be used in an intelligent sensor system. Chapter 3 3.1 Sensor selection The function of a sensor is to receive some action from a single phenomenon of the subject of measurement and to convert this to another physical phenomenon that can be more easily handled. The phenomenon constituting the subject of measurement is called the input signal, and the phenomenon after conversion is called the output signal. The ratio of the output signal to the input signal is called the transmittance or gain. Since the first function of a sensor is to convert changes in the subject of measurement to a physical phenomenon that can be more easily handled, i.e. its function consists in primary conversion, its conversion efficiency, or the degree of difficulty in delivering the output signal to the transducer constituting the next stage is of secondary importance The first point to which attention must be paid in sensor selection is to preserve as far as possible the information of the input signal. This is equivalent to preventing lowering of the signal-to-noise ratio (SNR). For example, if the SNR of the input signal is 60 dB, a sensor of dynamic range less than 60 dB should not be used. In order to detect changes in the quantity being measured as faithfully as possible, a sensor is required to have the following properties. Non-interference. This means that its output should not be changed by factors other than changes in the subject of measurement. Conversion satisfying this condition is called direct measurement. Conversion wherein the measurement quantity is found by calculation from output signals determined under the influence of several input signals is called indirect measurement. High sensitivity. The amount of change of the output signal that is produced by a change of unit amount of the input quantity being measured, i.e. the gain, should be as large as possible. Small measurement pressure. This means that the sensor should not disturb the physical conditions of the subject of measurement. From this point of view, modulation conversion offers more freedom than direct-acting conversion. High speed. The sensor should have sufficiently high speed of reaction to track the maximum anticipated rate of variation of the measured quantity. Low noise. The noise generated by the sensor itself should be as little as possible. Robustness. The output signal must be at least more robust than the quantity being measured, and be easier to handle. Robustness means resistance to environmental changes and/or noise. In general, phenomena of large energy are more resistant to external disturbance such as noise than are phenomena of smaller energy, they are easier to handle, and so have better robustness. If a sensor can be obtained that satisfies all these conditions, there is no problem. However, in practice, one can scarcely expect to obtain a sensor satisfying all these conditions. In such cases, it is necessary to combine the sensor with a suitable compensation mechanism, or to compensate the transducer of the secondary converter. Progress in IC manufacturing technology has made it possible to integrate various sensor functions. With the progressive shift from mainframes to minicomputers and hence to microcomputers, control systems have changed from centralized processing systems to distributed processing systems. Sensor technology has also benefited from such progress in IC manufacturing technology, with the result that systems whereby information from several sensors is combined and processed have changed from centralized systems to dispersed systems. Specifically, attempts are being made to use silicon-integrated sensors in a role combining primary data processing and input in systems that measure and process two-dimensional information such as picture information. This is a natural application of silicon precision working technology and digital circuit technology, which have been greatly advanced by introduction of VLSI manufacturing technology. Three-dimensional integrated circuits for recognizing letter patterns and odour sensors, etc., are examples of this. Such sensor systems can be called perfectly intelligent sensors in that they themselves have a certain data processing capability. It is characteristic of such sensors to combine several sensor inputs and to include a microprocessor that performs data processing. Their output signal is not a simple conversion of the input signal, but rather an abstract quantity obtained by some reorganization and combination of input signals from several sensors. This type of signal conversion is now often performed by a distributed processing mechanism, in which microprocessors are used to carry out the data processing that was previously performed by a centralized computer system having a large number of interfaces to individual sensors. However, the miniaturization obtained by application of integrated circuit techniques brings about an increase in the flexibility of coupling between elements. This has a substantial effect. Sensors of this type constitute a new technology that is at present being researched and developed. Although further progress can be expected, the overall picture cannot be predicted at the present time. Technically, practically free combinations of sensors can be implemented with the object of so-called indirect measurement, in which the signals from several individual sensors that were conventionally present are collected and used as the basis for a new output signal. In many aspects, new ideas are required concerning determination of the object of measurement, i.e. which measured quantities are to be selected, determination of the individual functions to achieve this, and the construction of the framework to organize these as a system. 3.2 Structure of an Intelligent Sensor The rapidity of development in microelectronics has had a profound effect on the whole of instrumentation science, and it has blurred some of the conceptual boundaries which once seemed so firm. In the present context the boundary between sensors and instruments is particularly uncertain. Processes which were once confined to a large electronic instrument are now available within the housing of a compact sensor, and it is some of these processes which we discuss later in this chapter. An instrument in our context is a system which is designed primarily to act as a free standing device for performing a particular set of measurements; the provision of communications facilities is of secondary importance. A sensor is a system which is designed primarily to serve a host system and without its communication channel it cannot serve its purpose. Nevertheless, the structures and processes used within either device, be they hardware or software, are similar. The range of disciplines which arc brought together in intelligent sensor system design is considerable, and the designer of such systems has to become something of a polymath. This was one of the problems in the early days of computer-aided measurement and there was some resistance from the backwoodsmen who practiced the art of measurement. 3.2.1 Elements of Intelligent Sensors The intelligent sensor is an example of a system, and in it we can identify a number of sub-systems whose functions are clearly distinguished from each other. The principal sub-systems within an intelligent sensor are: A primary sensing element Excitation Control Amplification (Possibly variable gain) Analogue filtering Data conversion Compensation Digital Information Processing Digital Communication Processing The figure illustrates the way in which these sub-systems relate to each other. Some of the realizations of intelligent sensors, particularly the earlier ones, may incorporate only some of these elements. The primary sensing element has an obvious fundamental importance. It is more than simply the familiar traditional sensor incorporated into a more up-to-date system. Not only are new materials and mechanisms becoming available for exploitation, but some of those that have been long known yet discarded because of various difficulties of behaviour may now be reconsidered in the light of the presence of intelligence to cope with these difficul ­ties. Excitation control can take a variety of forms depending on the circumstances. Some sensors, such as the thermocouple, convert energy directly from one form to another without the need for additional excitation. Others may require fairly elaborate forms of supply. It may be alternating or pulsed for subsequent coherent or phase-sensitive detection. In some circumstances it may be necessary to provide extremely stable supplies to the sensing element, while in others it may be necessary for those supplies to form part of a control loop to maintain the operating condition of the clement at some desired optimum. While this aspect may not be thought fundamental to intelligent sensors there is a largely unexplored range of possibilities for combining it with digital processing to produce novel instrumentation techniques. Amplification of the electrical output of the primary sensing element is almost invariably a requirement. This can pose design problems where high gain is needed. Noise is a particular hazard, and a circumstance unique to the intelligent form of sensor is the presence of digital buses carrying signals with sharp transitions. For this reason circuit layout is a particularly important part of the design process. Analogue filtering is required at minimum to obviate aliasing effects in the conversion stage, but it is also attractive where digital filtering would lake up too much of the real-time processing power available. Data conversion is the stage of transition between the continuous real world and the discrete internal world of the digital processor. It is important to bear in mind that the process of analogue to digital conversion is a non-linear one and represents a potentially gross distortion of the incoming information. It is important, however, for the intelligent sensor designer always to remember that this corruption is present, and in certain circumstances it can assume dominating importance. Such circumstances would include the case where the conversion process is part of a control loop or where some sort of auto-ranging, overt or covert, is built in to the operational program. Compensation is an inevitable part of the intelligent sensor. The operating point of the sensors may change due to various reasons. One of them is temperature. So an intelligent sensor must have an inbuilt compensation setup to bring the operating point back to its standard set stage. Information processing is, of course, unique to the intelligent form of sensor. There is some overlap between compensation and information processing, but there are also significant areas on independence. An important aspect is the condensation of information, which is necessary to preserve the two most precious resources of the industrial measurement system, the information bus and the central processor. A prime example of data condensa ­tion occurs in the Doppler velocimctcr in which a substantial quantity of informa ­tion is reduced to a single number representing the velocity. Sensor compensation will in general require the processi Development of Intelligent Sensor System Development of Intelligent Sensor System Chapter 1 1.1 Introduction What is Automation? Automation in general, can be explained as the use of computers or microcontrollers to control industrial machinery and processes thereby fully replacing human operators. Automation is a kind of transition from mechanization. In mechanization, human operators are provided with machinery to assist their operations, where as automation fully replaces the human operators with computers. The advantages of automation are: Increased productivity and higher production rates. Better product quality and efficient use of resources. Greater control and consistency of products. Improved safety and reduced factory lead times. Home Automation Home automation is the field specializing in the general and specific automation requirements of homes and apartments for their better safety, security and comfort of its residents. It is also called Domotics. Home automation can be as simple as controlling a few lights in the house or as complicated as to monitor and to record the activities of each resident. Automation requirements depend on person to person. Some may be interested in the home security while others will be more into comfort requirements. Basically, home automation is anything that gives automatic control of things in your house. Some of the commonly used features in home automation are: Control of lighting. Climate control of rooms. Security and surveillance systems. Control of home entertainment systems. House plant watering system. Overhead tank water level controllers. Intelligent Sensors Complex large-scale systems consist of a large number of interconnected components. Mastering the dynamic behavior of such systems, calls for distributed control architectures. This can be achieved by implementing control and estimation algorithms in several controllers. Some algorithms manipulate only local variables (which are available in the local interface) but in most cases, algorithms implemented in some given computing device will use variables which are available in this devices local interface, and also variables which are input to the control system via remote interfaces, thus rising the need for communication networks, whose architecture and complexity depend on the amount of data to be exchanged, and on the associated time constraints. Associating computing (and communication) devices with sensing or actuating functions, has given rise to intelligent sensors. These sensors have gained a huge success in the past ten years, especially with the development of neural network s, fuzzy logic, and soft computing algorithms. The modern definition of smart or intelligent sensors can be formulated now as: ‘Smart sensor is an electronic device, including sensing element, interfacing, signal processing and having several intelligence functions as self-testing, self-identification, self-validation or self-adaptation. The keyword in this definition is ‘intelligence. The self-adaptation is a relatively new function of smart sensors and sensor systems. Self-adaptation smart sensors and systems are based on so-called adaptive algorithms and directly connected with precision measurements of frequency-time parameters of electrical signals. The later chapters will give an elaborate view on why we should use intelligent sensors, intelligent sensor structure, characteristics and network standards. Chapter 2 2.1 Conventional Sensors Before talking more on intelligent sensors, first we need to examine regular sensors in order to obtain a solid foundation on which we can develop our understanding on intelligent sensors. Most of the conventional sensors have shortcomings, both technically and economically. For a sensor to work effectively, it must be calibrated. That is, its output must be made to match some predetermined standard so that its reported values correctly reflect the parameter being measured. In the case of a bulb thermometer, the graduations next to the mercury column must be positioned so that they accurately correspond to the level of mercury for a given temperature. If the sensor is not calibrated, the information that it reports wont be accurate, which can be a big problem for the systems that use the reported information. The second concern one has when dealing with sensors is that their properties usually change over time, a phenomenon knows as drift. For instance, suppose we are measuring a DC current in a particular part of a circuit by monitoring the voltage across a resistor in that circuit. In this case, the sensor is the resistor and the physical property that we are measuring the voltage across it. As the resistor ages, its chemical properties will change, thus altering its resistance. As with the issue of calibration, some situations require much stricter drift tolerances than others; the point is that sensor properties will change with time unless we compensate for the drift in some fashion, and these changes are usually undesirable. The third problem is that not only do sensors themselves change with time, but so, too, does the environment in which they operate. An excellent example of that would be the electronic ignition for an internal combustion engine. Immediately after a tune-up, all the belts are tight, the spark plugs are new, the fuel injectors are clean, and the air filter is pristine. From that moment on, things go downhill; the belts loosen, deposits build up on the spark plugs and fuel injectors, and the air filter becomes clogged with ever-increasing amounts of dirt and dust. Unless the electronic ignition can measure how things are changing and make adjustments, the settings and timing sequence that it uses to fire the spark plugs will become progressively mismatched for the engine conditions, resulting in poorer performance and reduced fuel efficiency. The ability to compensate for often extreme changes in the operating environment makes a huge difference in a sensors value to a particular applic ation. Yet a fourth problem is that most sensors require some sort of specialized hardware called signal-conditioning circuitry in order to be of use in monitoring or control applications. The signal-conditioning circuitry is what transforms the physical sensor property that were monitoring (often an analog electrical voltage that varies in some systematic way with the parameter being measured) into a measurement that can be used by the rest of the system. Depending upon the application, the signal conditioning may be as simple as a basic amplifier that boosts the sensor signal to a usable level or it may entail complex circuitry that cleans up the sensor signal and compensates for environmental conditions, too. Frequently, the conditioning circuitry itself has to be tuned for the specific sensor being used, and for analog signals that often means physically adjusting a potentiometer or other such trimming device. In addition, the configuration of the signal-conditioning circuitry tends to be unique to both the specific type of sensor and to the application itself, which means that different types of sensors or different applications frequently need customized circuitry. Finally, standard sensors usually need to be physically close to the control and monitoring systems that receive their measurements. In general, the farther a sensor is from the system using its measurements, the less useful the measurements are. This is due primarily to the fact that sensor signals that are run long distances are susceptible to electronic noise, thus degrading the quality of the readings at the receiving end. In many cases, sensors are connected to the monitoring and control systems using specialized (and expensive) cabling; the longer this cabling is, the more costly the installation, which is never popular with end users. A related problem is that sharing sensor outputs among multiple systems becomes very difficult, particularly if those systems are physically separated. This inability to share outputs may not seem important, but it severely limits the ability to scale systems to large installations, resulting in much higher costs to install and support multiple r edundant sensors. What we really need to do is to develop some technique by which we can solve or at least greatly alleviate these problems of calibration, drift, and signal conditioning. 2.2 Making Sensors Intelligent Control systems are becoming increasingly complicated and generate increasingly complex control information. Control must nevertheless be exercised, even under such circumstances. Even considering just the detection of abnormal conditions or the problems of giving a suitable warning, devices are required that can substitute for or assist human sensation, by detecting and recognizing multi-dimensional information, and conversion of non visual information into visual form. In systems possessing a high degree of functionality, efficiency must be maximized by division of the information processing function into central processing and processing dispersed to local sites. With increased progress in automation, it has become widely recognized that the bottleneck in such systems lies with the sensors. Such demands are difficult to deal with by simply improvising the sensor devices themselves. Structural reinforcement, such as using array of sensors, or combinations of different types of sensors, and reinforcement from the data processing aspect by a signal processing unit such as a computer, are indispensible. In particular, the data processing and sensing aspects of the various stages involved in multi-dimensional measurement, image construction, characteristic extraction and pattern recognition, which were conventionally performed exclusively by human beings, have been tremendously enhanced by advances in micro-electronics. As a result, in many cases sensor systems have been implemented that substitute for some or all of the intellectual actions of human beings, i.e. intelligent sensor systems. Sensors which are made intelligent in this way are called ‘intelligent sensors or ‘smart sensors. According to Breckenridge and Husson, the smart sensor itself has a data processing function and automatic calibration/automatic compensation function, in which the sensor itself detects and eliminates abnormal values or exceptional values. It incorporates an algorithm, which is capable of being altered, and has a certain degree of memory function. Further desirable characteristics are that the sensor is coupled to other sensors, adapts to changes in environmental conditions, and has a discriminant function. Scientific measuring instruments that are employed for observation and measurement of physical world are indispensible extensions of our senses and perceptions in the scientific examination of nature. In recognizing nature, we mobilize all the resources of information obtained from the five senses of sight, hearing, touch, taste and smell etc. and combine these sensory data in such a way as to avoid contradiction. Thus more reliable, higher order data is obtained by combining data of different types. That is, there is a data processing mechanism that combines and processes a number of sensory data. The concept of combining sensors to implement such a data processing mechanism is called ‘sensor fusion 2.2.1 Digitizing the Sensor Signal The discipline of digital signal processing or DSP, in which signals are manipulated mathematically rather than with electronic circuitry, is well established and widely practiced. Standard transformations, such as filtering to remove unwanted noise or frequency mappings to identify particular signal components, are easily handled using DSP. Furthermore, using DSP principles we can perform operations that would be impossible using even the most advanced electronic circuitry. For that very reason, todays designers also include a stage in the signal-conditioning circuitry in which the analog electrical signal is converted into a digitized numeric value. This step, called analog-to-digital conversion, A/D conversion, or ADC, is vitally important, because as soon as we can transform the sensor signal into a numeric value, we can manipulate it using software running on a microprocessor. Analog-to-digital converters, or ADCs as theyre referred to, are usually single-chip semiconductor devices that can be made to be highly accurate and highly stable under varying environmental conditions. The required signal-conditioning circuitry can often be significantly reduced, since much of the environmental compensation circuitry can be made a part of the ADC and filtering can be performed in software. 2.2.2 Adding Intelligence Once the sensor signal has been digitized, there are two primary options in how we handle those numeric values and the algorithms that manipulate them. We can either choose to implement custom digital hardware that essentially â€Å"hard-wires† our processing algorithm, or we can use a microprocessor to provide the necessary computational power. In general, custom hardware can run faster than microprocessor-driven systems, but usually at the price of increased production costs and limited flexibility. Microprocessors, while not necessarily as fast as a custom hardware solution, offer the great advantage of design flexibility and tend to be lower-priced since they can be applied to a variety of situations rather than a single application. Once we have on-board intelligence, were able to solve several of the problems that we noted earlier. Calibration can be automated, component drift can be virtually eliminated through the use of purely mathematical processing algorithms, and we can compensate for environmental changes by monitoring conditions on a periodic basis and making the appropriate adjustments automatically. Adding a brain makes the designers life much easier. 2.2.3 Communication Interface The sharing of measurements with other components within the system or with other systems adds to the value of these measurements. To do this, we need to equip our intelligent sensor with a standardized means to communicate its information to other elements. By using standardized methods of communication, we ensure that the sensors information can be shared as broadly, as easily, and as reliably as possible, thus maximizing the usefulness of the sensor and the information it produces. Thus these three factors consider being mandatory for an intelligent sensor: A sensing element that measures one or more physical parameters (essentially the traditional sensor weve been discussing), A computational element that analyzes the measurements made by the sensing element, and A communication interface to the outside world that allows the device to exchange information with other components in a larger system. Its the last two elements that really distinguish intelligent sensors from their more common standard sensor relatives because they provide the abilities to turn data directly into information, to use that information locally, and to communicate it to other elements in the system. 2.3 Types of Intelligent Sensors Intelligent sensors are chosen depending on the object, application, precision system, environment of use and cost etc. In such cases consideration must be given as to what is an appropriate evaluation standard. This question involves a multi-dimensional criterion and is usually very difficult. The evaluation standard directly reflects the sense of value itself applied in the design and manufacture of the target system. This must therefore be firmly settled at the system design stage. In sensor selection, the first matter to be considered is determination of the subject of measurement. The second matter to be decided on is the required precision and dynamic range. The third is ease of use, cost, delivery time etc., and ease of maintenance in actual use and compatibility with other sensors in the system. The type of sensor should be matched to such requirements at the design stage. Sensors are usually classified by the subject of measurement and the principle of sensing action. 2.3.1 Classification Based on Type of Input In this, the sensor is classified in accordance with the physical phenomenon that is needed to be detected and the subject of measurement. Some of the examples include voltage, current, displacement and pressure. A list of sensors and their categories are mentioned in the following table. Category Type Dynamic Quantity Flow rate, Pressure, force, tension Speed, acceleration Sound, vibration Distortion, direction proximity Optical Quantities Light (infra red, visible light or radiation) Electromagnetic Quantities Current, voltage, frequency, phase, vibration, magnetism Quantity of Energy or Heat Temperature, humidity, dew point Chemical Quantities Analytic sensors, gas, odour, concentration, pH, ions Sensory Quantities or Biological Quantities Touch, vision, smell Table 2.3.1: Sensed items Classified in accordance with subject of measurement. 2.3.2 Classification Based on Type of Output In an intelligent sensor, it is often necessary to process in an integrated manner the information from several sensors or from a single sensor over a given time range. A computer of appropriate level is employed for such purposes in practically y all cases. For coupling to the computer when constructing an intelligent sensor system, a method with a large degree of freedom is therefore appropriate. It is also necessary to pay careful attention to the type of physical quantity carrying the output information to the sensor, and to the information description format of this physical quantity or dynamic quantity, and for the description format an analog, digital or encoded method etc., might be used. Although any physical quantities could be used as output signal, electrical quantities such as voltage are more convenient for data input to a computer. The format of the output signal can be analog or digital. For convenience in data input to the computer, it is preferable if the output signal of the sensor itself is in the form of a digital electrical signal. In such cases, a suitable means of signal conversion must be provided to input the data from the sensor to the computer 2.3.3 Classification Based on Accuracy When a sensor system is constructed, the accuracy of the sensors employed is a critical factor. Usually sensor accuracy is expressed as the minimum detectable quantity. This is determined by the sensitivity of the sensor and the internally generated noise of the sensor itself. Higher sensitivity and lower internal noise level imply greater accuracy. Generally for commercially available sensors the cost of the sensor is determined by the accuracy which it is required to have. If no commercial sensor can be found with the necessary accuracy, a custom product must be used, which will increase the costs. For ordinary applications an accuracy of about 0.1% is sufficient. Such sensors can easily be selected from commercially available models. Dynamic range (full scale deflection/minimum detectable quantity) has practically the same meaning as accuracy, and is expressed in decibel units. For example a dynamic range of 60dB indicates that the full scale deflection is 103 times the minimum detectable quantity. That is, a dynamic range of 60dB is equivalent to 0.1% accuracy. In conventional sensors, linearity of output was regarded as quite important. However, in intelligent sensor technology the final stage is normally data processing by computer, so output linearity is not a particular problem. Any sensor providing a reproducible relationship of input and output signal can be used in an intelligent sensor system. Chapter 3 3.1 Sensor selection The function of a sensor is to receive some action from a single phenomenon of the subject of measurement and to convert this to another physical phenomenon that can be more easily handled. The phenomenon constituting the subject of measurement is called the input signal, and the phenomenon after conversion is called the output signal. The ratio of the output signal to the input signal is called the transmittance or gain. Since the first function of a sensor is to convert changes in the subject of measurement to a physical phenomenon that can be more easily handled, i.e. its function consists in primary conversion, its conversion efficiency, or the degree of difficulty in delivering the output signal to the transducer constituting the next stage is of secondary importance The first point to which attention must be paid in sensor selection is to preserve as far as possible the information of the input signal. This is equivalent to preventing lowering of the signal-to-noise ratio (SNR). For example, if the SNR of the input signal is 60 dB, a sensor of dynamic range less than 60 dB should not be used. In order to detect changes in the quantity being measured as faithfully as possible, a sensor is required to have the following properties. Non-interference. This means that its output should not be changed by factors other than changes in the subject of measurement. Conversion satisfying this condition is called direct measurement. Conversion wherein the measurement quantity is found by calculation from output signals determined under the influence of several input signals is called indirect measurement. High sensitivity. The amount of change of the output signal that is produced by a change of unit amount of the input quantity being measured, i.e. the gain, should be as large as possible. Small measurement pressure. This means that the sensor should not disturb the physical conditions of the subject of measurement. From this point of view, modulation conversion offers more freedom than direct-acting conversion. High speed. The sensor should have sufficiently high speed of reaction to track the maximum anticipated rate of variation of the measured quantity. Low noise. The noise generated by the sensor itself should be as little as possible. Robustness. The output signal must be at least more robust than the quantity being measured, and be easier to handle. Robustness means resistance to environmental changes and/or noise. In general, phenomena of large energy are more resistant to external disturbance such as noise than are phenomena of smaller energy, they are easier to handle, and so have better robustness. If a sensor can be obtained that satisfies all these conditions, there is no problem. However, in practice, one can scarcely expect to obtain a sensor satisfying all these conditions. In such cases, it is necessary to combine the sensor with a suitable compensation mechanism, or to compensate the transducer of the secondary converter. Progress in IC manufacturing technology has made it possible to integrate various sensor functions. With the progressive shift from mainframes to minicomputers and hence to microcomputers, control systems have changed from centralized processing systems to distributed processing systems. Sensor technology has also benefited from such progress in IC manufacturing technology, with the result that systems whereby information from several sensors is combined and processed have changed from centralized systems to dispersed systems. Specifically, attempts are being made to use silicon-integrated sensors in a role combining primary data processing and input in systems that measure and process two-dimensional information such as picture information. This is a natural application of silicon precision working technology and digital circuit technology, which have been greatly advanced by introduction of VLSI manufacturing technology. Three-dimensional integrated circuits for recognizing letter patterns and odour sensors, etc., are examples of this. Such sensor systems can be called perfectly intelligent sensors in that they themselves have a certain data processing capability. It is characteristic of such sensors to combine several sensor inputs and to include a microprocessor that performs data processing. Their output signal is not a simple conversion of the input signal, but rather an abstract quantity obtained by some reorganization and combination of input signals from several sensors. This type of signal conversion is now often performed by a distributed processing mechanism, in which microprocessors are used to carry out the data processing that was previously performed by a centralized computer system having a large number of interfaces to individual sensors. However, the miniaturization obtained by application of integrated circuit techniques brings about an increase in the flexibility of coupling between elements. This has a substantial effect. Sensors of this type constitute a new technology that is at present being researched and developed. Although further progress can be expected, the overall picture cannot be predicted at the present time. Technically, practically free combinations of sensors can be implemented with the object of so-called indirect measurement, in which the signals from several individual sensors that were conventionally present are collected and used as the basis for a new output signal. In many aspects, new ideas are required concerning determination of the object of measurement, i.e. which measured quantities are to be selected, determination of the individual functions to achieve this, and the construction of the framework to organize these as a system. 3.2 Structure of an Intelligent Sensor The rapidity of development in microelectronics has had a profound effect on the whole of instrumentation science, and it has blurred some of the conceptual boundaries which once seemed so firm. In the present context the boundary between sensors and instruments is particularly uncertain. Processes which were once confined to a large electronic instrument are now available within the housing of a compact sensor, and it is some of these processes which we discuss later in this chapter. An instrument in our context is a system which is designed primarily to act as a free standing device for performing a particular set of measurements; the provision of communications facilities is of secondary importance. A sensor is a system which is designed primarily to serve a host system and without its communication channel it cannot serve its purpose. Nevertheless, the structures and processes used within either device, be they hardware or software, are similar. The range of disciplines which arc brought together in intelligent sensor system design is considerable, and the designer of such systems has to become something of a polymath. This was one of the problems in the early days of computer-aided measurement and there was some resistance from the backwoodsmen who practiced the art of measurement. 3.2.1 Elements of Intelligent Sensors The intelligent sensor is an example of a system, and in it we can identify a number of sub-systems whose functions are clearly distinguished from each other. The principal sub-systems within an intelligent sensor are: A primary sensing element Excitation Control Amplification (Possibly variable gain) Analogue filtering Data conversion Compensation Digital Information Processing Digital Communication Processing The figure illustrates the way in which these sub-systems relate to each other. Some of the realizations of intelligent sensors, particularly the earlier ones, may incorporate only some of these elements. The primary sensing element has an obvious fundamental importance. It is more than simply the familiar traditional sensor incorporated into a more up-to-date system. Not only are new materials and mechanisms becoming available for exploitation, but some of those that have been long known yet discarded because of various difficulties of behaviour may now be reconsidered in the light of the presence of intelligence to cope with these difficul ­ties. Excitation control can take a variety of forms depending on the circumstances. Some sensors, such as the thermocouple, convert energy directly from one form to another without the need for additional excitation. Others may require fairly elaborate forms of supply. It may be alternating or pulsed for subsequent coherent or phase-sensitive detection. In some circumstances it may be necessary to provide extremely stable supplies to the sensing element, while in others it may be necessary for those supplies to form part of a control loop to maintain the operating condition of the clement at some desired optimum. While this aspect may not be thought fundamental to intelligent sensors there is a largely unexplored range of possibilities for combining it with digital processing to produce novel instrumentation techniques. Amplification of the electrical output of the primary sensing element is almost invariably a requirement. This can pose design problems where high gain is needed. Noise is a particular hazard, and a circumstance unique to the intelligent form of sensor is the presence of digital buses carrying signals with sharp transitions. For this reason circuit layout is a particularly important part of the design process. Analogue filtering is required at minimum to obviate aliasing effects in the conversion stage, but it is also attractive where digital filtering would lake up too much of the real-time processing power available. Data conversion is the stage of transition between the continuous real world and the discrete internal world of the digital processor. It is important to bear in mind that the process of analogue to digital conversion is a non-linear one and represents a potentially gross distortion of the incoming information. It is important, however, for the intelligent sensor designer always to remember that this corruption is present, and in certain circumstances it can assume dominating importance. Such circumstances would include the case where the conversion process is part of a control loop or where some sort of auto-ranging, overt or covert, is built in to the operational program. Compensation is an inevitable part of the intelligent sensor. The operating point of the sensors may change due to various reasons. One of them is temperature. So an intelligent sensor must have an inbuilt compensation setup to bring the operating point back to its standard set stage. Information processing is, of course, unique to the intelligent form of sensor. There is some overlap between compensation and information processing, but there are also significant areas on independence. An important aspect is the condensation of information, which is necessary to preserve the two most precious resources of the industrial measurement system, the information bus and the central processor. A prime example of data condensa ­tion occurs in the Doppler velocimctcr in which a substantial quantity of informa ­tion is reduced to a single number representing the velocity. Sensor compensation will in general require the processi